1. Field of the Invention
The field of this invention relates to household appliances and, more particularly, to clothes washing machines and to automatic detecting of clothes fabric type in clothes washers.
2. Background
Partial or fully automated control of the operation of clothes washing machines is seen as being desirable from the standpoint of, for example, improving energy efficiency, optimizing usage of water, and providing optimal clothes care. One parameter or factor affecting the ability to automate and optimize the control of the washing machine is the blend of clothes or fabric type (e.g., cotton, polyester), which varies with each washer usage. Detection of the clothes blend in a given washer load would enable an automated washer controller to control various operating states to optimize clothes care and minimize energy usage, for example, by setting the proper amount of water, the proper water temperature, the amount of detergent to be added, and the amount of mechanical washing action to supply to the clothes. Detection of the proportion of each fabric type in a particular clothes load by direct means is not, however, presently seen as being economically feasible for an appliance in the price range of a washing machine, and, therefore, indirect means or methods of sensing the clothes blend making up each load have been proposed.
U.S. Pat. No. 5,241,845, to Ishibashi et al., discloses a washing machine that employs a neural network to determine the appropriate agitation pattern and washing time based on several inputs, including clothes volume and clothes type. Clothes volume and type are inferred from a measurement of the phase angle of the driving motor.
Merloni Elettrodomestica produces a washing machine that estimates the quantity of the clothes load and the fabric type. The load and fabric type are inferred from the rate of change of the water level sensor. Cotton fabric will, for example, absorb water at a much faster rate than will synthetic fibers, such as polyester. Operating conditions in this washing machine, in particular washing time and water temperature, are determined, at least in part, by factors in addition to clothes load and fabric type, for example, by measuring the conductivity of the water to determine its hardness, and including that as a control input. A washing machine produced by AEG of Germany uses a similar approach, in using the rate of change of water level to determine clothes load and type.
U.S. Pat. No. 5,161,393, issued to Payne et al., and assigned to the assignee of the present application, discloses a method for fabric blend sensing that uses the average motor torque of a switched reluctance motor (SRM) during a number of agitation cycles as a measure of clothes load.
This method, as well as others reported in the literature in general, rely on the use of expensive motor control and sensing circuitry in estimating the clothes or fabric blend.
A need continues to exist in the art to automatically detect, by accurate estimation, the blend of fabric types present in loads to be washed, without significantly increasing the overall sensor cost for the washing machine.